In high occupancy vehicle (HOV) lane and high occupancy tolling (HOT) systems, vehicle operators are incentivized to “car pool” by allowing high occupancy vehicles to use certain lanes that tend to be less congested or to pay reduced toll fees. HOV and HOT systems, thus, promise better highway utilization and reduced traffic congestion when HOV and HOT rules are observed by vehicle operators. In practice, however, the enforcement of HOV and HOT systems is difficult, and violation rates of up to 65% have been reported. Current enforcement methods include relying on law enforcement to visually observe vehicles, visually determine potential violators, and then pull over such vehicles to determine actual violation status and, if appropriate, take official action, such as issuing a ticket. This approach can be dangerous, especially in the context of fast highway conditions and tight spaces. It is also frequently ineffective, and enforcement rates of only 10% are typical.
In addition, law enforcement may pull vehicles over that were erroneously determined to be violating one of more HOV rules as the result of difficult to observe passengers, such as children riding in rear seats, leading to “false positives.” Such false positives are not only great nuisances to HOV-abiding vehicle operators, but they also effectively waste the limited resources of law enforcement, which may be able to pull over only a subset of candidate violators, thus allowing other, actual violators to avoid detection during the time that law enforcement is reacting to false positives. This conventional approach also suffers from the drawback that, by relying on human operators (i.e., law enforcement, which may comprise a rotating array of different police officers, each with different memory and abilities), it cannot take into account historical patterns with respect to individual vehicles' compliance with or violation of HOV or HOT rules, which may provide a guide as to whether a given vehicle is presently violating HOV or HOT rules.
Accordingly, there is a need for methods and systems for utilizing historical information about individual vehicles' compliance with or violation of HOV or HOT rules, including previous false positives or actual violations, to improve the accuracy of hypotheses as to whether the same vehicles may be presently violating one or more HOV or HOT rules.